Method and system for x-ray image generation

ABSTRACT

A method of creating an image including retrieving three-dimensional image data of an anatomy, retrieving a model of a portion of the anatomy, associating the model with the three-dimensional image data such that the model defines a bounded volume within the three-dimensional image data corresponding to the portion of the anatomy, and creating a virtual radiograph of the portion of the anatomy. Creating the virtual radiograph includes casting a plurality of rays from an origin point through the bounded volume, sampling, for each ray, the bounded volume at a plurality of sampling steps along the ray, the sampling steps separated by a sampling distance, and calculating, for each ray, an accumulated attenuation value of the bounded volume along the ray based on the samples.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/257,622, filed Sep. 6, 2016, which is a divisional of U.S.application Ser. No. 13/948,592, filed Jul. 23, 2013. Each of theaforementioned applications is incorporated herein by reference in itsentirety.

BACKGROUND

The present disclosure generally relates to the field of x-rayvisualization. The present disclosure relates more specifically to thecreation of two-dimensional x-ray images for providing assistive viewsin preparation for an operation.

Medical professionals may be accustomed to using traditional x-rayimages in surgical planning methods, and accordingly, it is desirable toprovide improvements for surgical planning and anatomy visualizationthat utilize the same types of images that medical professionals arecomfortable with. At the same time, there are limitations to usingtraditional x-ray models, such as the inability to correct the positionof the patient's anatomy in the anatomy image. In surgical planning, itmay be desirable to have the target anatomy in a particular position,but an x-ray image is limited to the position of the patient on thex-ray table when the image is created. Furthermore, traditional x-rayimages cannot be manipulated to show rotated/repositioned anatomy orimplants, such as orthopedic joint prostheses, in an x-ray image toprovide a guide for surgical planning and for comparison with apost-operative record.

SUMMARY

One implementation of the present disclosure relates to a method ofcreating an image. The method includes providing three-dimensional imagedata of an anatomy, providing a model of a portion of the anatomy, andcreating a virtual radiograph of a target portion of the anatomy usinginformation from the image data and information from the model.

In some embodiments, the method may include representing a portion ofthe anatomy in a modified state on the virtual radiograph, and themodified state may be a translation or rotation, or a resection, of theportion of the anatomy. The portion of the anatomy may be modifiedaccording to a preoperative plan.

In some embodiments, the method may include subtracting image datacorresponding to the portion of the anatomy from the virtual radiograph.The virtual radiograph may further be created by modifying image datacorresponding to the portion of the anatomy and adding the modifiedimage data to the virtual radiograph.

In some embodiments, the method may include adding an image of aprosthetic device to the virtual radiograph. The image of the prostheticdevice may be added to the virtual radiograph according to apreoperative plan.

In some embodiments, the model of a portion of the anatomy is asegmented bone model. In other embodiments, the model may provide aboundary of the portion of the anatomy within the three-dimensionalimage data.

In some embodiments, creating the virtual radiograph may includeexecuting a first volume ray casting process on the three-dimensionalimage data, and may include executing a second volume ray castingprocess on the three-dimensional image data bounded by the model. Thecreating the virtual radiograph may include calculating first set ofaccumulated attenuation values during the first volume ray castingprocess, adding the first set of accumulated attenuation values to thevirtual radiograph, calculating a second set of accumulated attenuationvalues during the second volume ray casting process, and subtracting thesecond set of accumulated attenuation values from the virtualradiograph. The creating the virtual radiograph may further includemodifying the second set of accumulated attenuation values according toa preoperative plan and adding the modified second set of accumulatedattenuation values to the virtual radiograph, and wherein the step ofcreating a virtual radiograph includes adding an image of a prostheticdevice to the virtual radiograph.

In some embodiments, creating the virtual radiograph may includeperforming a third volume ray casting process on an implant model,calculating a third set of accumulated attenuation values from the thirdvolume ray casting process, and adding the third set of accumulatedattenuation values to the difference of the first and second sets ofaccumulated attenuation values. The method may further include whereinthe implant model is positioned and oriented relative to thethree-dimensional image data, the model, or the portion of the anatomyaccording to a preoperative plan.

Another implementation of the present disclosure is an image generationsystem including a processing circuit having a processor and a memory,an input/output interface, a display coupled to the input/outputinterface. The processing circuit is configured to retrievethree-dimensional image data of an anatomy, retrieve a model of ananatomy corresponding to a portion of the anatomy, create a virtualradiograph using information from the three-dimensional image data andthe model, and display the resultant virtual radiograph on the display.

In other embodiments, the processing circuit is further configured tomodify the portion of the anatomy according to a preoperative plan. Theprocessing circuit may be further configured to display, in the virtualradiograph, the portion of the anatomy in a modified state.

In other embodiments, the processing circuit is further configured tosubtract image data corresponding to the portion of the anatomy from thevirtual radiograph, and may be configured to modify the image datacorresponding to the portion of the anatomy, and may be furtherconfigured to add the modified image data corresponding to the portionof the anatomy to the virtual radiograph. The processing circuit may beconfigured to modify the image data corresponding to the portion of theanatomy according to a preoperative plan.

In other embodiments, the processing circuit is further configured toadd a virtual image of a prosthetic device to the virtual radiograph.

Another implementation of the present disclosure is a method forgenerating a virtual radiograph for display on a display device. Themethod includes providing an image generation system having a processingcircuit including a processor and a memory device, the image generationsystem coupled to the display device, retrieving three-dimensional imagedata of an anatomy stored in the memory, retrieving a three-dimensionalbone model corresponding to a portion of the anatomy stored in thememory, associating the three-dimensional bone model with thethree-dimensional image data such that the three-dimensional bone modeldefines first boundary containing a first bounded volume within thethree-dimensional image data corresponding to the portion of theanatomy, and performing a volume ray casting process on thethree-dimensional image data. The volume ray casting process includescasting a ray from an origin point through a first pixel in a screenspace rectangle, and through the first bounded volume, sampling thefirst bounded volume at a plurality of sampling steps along the ray, thesampling steps separated by a sampling distance, wherein the sampling islimited to a segment of the ray between a position proximate to a frontfacing intersection of the ray and the first boundary, and a positionproximate to a back facing intersection of the ray and the firstboundary, computing an attenuation coefficient of the ray at each of thesampling steps based upon the sample at each of the sampling steps,calculating a first accumulated attenuation value of the first boundedvolume along the ray, casting a second ray along a second pixel of thescreen space rectangle, repeating the sampling, computing, andcalculating steps for the second pixel of the screen space rectangle tocalculate a second accumulated attenuation value of the first boundedvolume, and storing the accumulated attenuation values of the firstbounded volume.

In other embodiments, the method further includes providing a secondboundary defining a second bounded volume of the three-dimensional imagedata, performing the volume ray casting process on the second boundedvolume of the three-dimensional image data, adding the accumulatedattenuation values of the second bounded volume to the virtualradiograph, and subtracting the accumulated attenuation values of thefirst bounded volume from the virtual radiograph.

In other embodiments, the method further includes modifying dataassociated with the first bounded volume. The data associated with thefirst bounded volume may include at least one of three-dimensional imagedata within the first bounded volume, the attenuation coefficients ofthe first bounded volume, the accumulated attenuation values of thefirst bounded volume, and color information associated with the firstbounded volume.

In other embodiments, the modification of data associated with the firstbounded volume includes at least one of translation, rotation, andresection. The modification of data may also be performed to correspondto a preoperative plan. The data associated with the first boundedvolume may be the accumulated attenuation values of the first boundedvolume, and further comprising adding the modified accumulatedattenuation values of the first bounded volume to the virtualradiograph.

In other embodiments, the method may include calculating attenuationvalues of an implant model and adding the attenuation values of theimplant model to the virtual radiograph. The implant model may bepositioned relative to the three dimensional image data according to apreoperative plan.

In other embodiments, the method may further include converting theaccumulated attenuation values of the first bounded volume to colorinformation and providing the color information to the display.

Alternative exemplary embodiments relate to other features andcombinations of features as may be generally recited in the claims.

BRIEF DESCRIPTION OF THE FIGURES

The disclosure will become more fully understood from the followingdetailed description, taken in conjunction with the accompanyingfigures, wherein like reference numerals refer to like elements, inwhich:

FIG. 1 is a block diagram of an image generation system, according to anexemplary embodiment;

FIG. 2 is a flow chart of an x-ray visualization process, according toan exemplary embodiment;

FIGS. 3A-D illustrate the x-ray visualization process of FIG. 2,according to an exemplary embodiment;

FIG. 4 is a flow chart of the ray casting process of the x-rayvisualization process of FIG. 2, according to an exemplary embodiment;

FIG. 5 is a flow chart of a process for computing an accumulatedattenuation for the ray casting process of FIG. 2, according to anexemplary embodiment;

FIGS. 6A-B illustrate the ray casting algorithm of FIG. 5, according toan exemplary embodiment;

FIG. 7 is a flow chart of a process for drawing constant attenuationmodels for the x-ray visualization process of FIG. 4, according to anexemplary embodiment;

FIGS. 8A-D illustrate the effect of various brightness and contrastvalues that may be set for an x-ray image, according to an exemplaryembodiment; and

FIG. 9 is an example user interface for which the image generationsystem may be implemented, according to an exemplary embodiment.

DETAILED DESCRIPTION

Before turning to the figures, which illustrate the exemplaryembodiments in detail, it should be understood that the application isnot limited to the details or methodology set forth in the descriptionor illustrated in the figures. It should also be understood that theterminology is for the purpose of description only and should not beregarded as limiting.

Referring generally to the figures, systems and methods for creation oftwo-dimensional (2-D) x-ray images are shown and described. The systemsand methods described herein may generally create interactivehigh-quality virtual radiographs, also referred to herein as x-rayimages, using a patient computed tomography (CT) scan, segmented bonemodels, and a preoperative plan for an operation. The x-ray imagesgenerated may provide a full antero-posterior view for implant planning(or any other surgical planning). The generated x-ray images may furtherbe used as a comparison with a post-operative record. The images aredisplayed on a user interface augmented with digital tools that mayassist a user during a preoperative surgical planning process.

In one embodiment, the systems and methods herein may be used to providea customizable view of the pelvis and femur of a patient. For example,an x-ray image of the pelvis and the femur may be created, then may bemanipulated in such a way to provide a pure antero-posterior or lateralperspective of the anatomy. This may provide an improvement ontraditional x-ray imaging techniques in that a limitation of traditionalx-ray imaging techniques relates to the effect of a patient's positionon the x-ray table. Further, implant models may be added to the x-rayimage to be utilized in preparation of the surgical plan and to be usedfor comparison with a post-operative record.

The x-ray images are manipulated to provide various views forpreparation in an operation. Referring generally to FIGS. 1-2, an imagegeneration system 100 and a process 200 executable by image generationsystem 100 are shown and described. Image generation system 100 maygenerally be configured to generate x-ray images for viewing by amedical professional. Image generation system 100 may be a componentintegrated with other medical-related software, according to oneembodiment.

System 100 may generate x-ray images using data representing the anatomyof a patient, such as a patient CT scan from an imaging system 132 or astatistical deformable model, segmented bone models, and a preoperativeplan for an operation. In one example of a preoperative plan a doctorand/or assistants to a doctor may map out anticipated tissue resections,implant placements, and/or other intended actions to be performed duringor outcomes to be realized from the surgery. System 100 may receive suchinformation from a user via an input/output (I/O) interface 108, and/orretrieve the information from a database 110. Segmented bone models maybe created by such methods as a livewire segmentation technique, Mimicssoftware, or other methods known in the art.

System 100 generally includes a processing circuit 102 having aprocessor 104 and memory 106. Processor 104 may be or include one ormore microprocessors, an application specific integrated circuit (ASIC),a circuit containing one or more processing components, a group ofdistributed processing components, circuitry for supporting amicroprocessor, or other hardware configured for processing. Accordingto an exemplary embodiment, processor 104 is configured to executecomputer code stored in memory 106 to complete and facilitate theactivities described herein. Memory 106 can be any volatile ornon-volatile memory device capable of storing data or computer coderelating to the activities described herein. For example, memory 106 isshown to include various modules which are computer code modules (e.g.,executable code, object code, source code, script code, machine code,etc.) configured for execution by processor 104. When executed byprocessor 104, processing circuit 102 is configured to complete theactivities described herein.

Memory 106 is shown to include various modules for executing process200. Process 200 for generating an x-ray image may generally include avolume ray casting component where additive and subtractive models aredrawn, a component for drawing constant attenuation models, and acomponent for computing the output color from the attenuation andthickness values computed by the first two components. Memory 106 isshown to include a volume ray casting module 112, an attenuation modelmodule 114, and a color module 116 for executing the components ofprocess 200. Ray casting module 112 may generally be configured torotate or resect one or more features in a provided CT scan image.Attenuation model module 114 may generally be configured to indicatesuch a feature in an x-ray image output by system 100, and color module116 may be configured to provide grayscale color settings for the imagefor display. The activities of modules 112-116 are described in greaterdetail below with respect to subsequent figures.

Memory 106 may include one or more buffers 118-124 for temporarilystoring data during the x-ray image generation process. Memory 106includes an attenuation buffer 118 for storing additive and subtractiveattenuation values computed during the ray casting process. Memory 106also includes a thickness buffer 120 for storing a thickness of inputmodels and a front buffer 122 and back buffer 124 to store XYZcoordinates of the front and back fragments of an input model. The useof buffers 118-124 are described in greater detail below with respect tosubsequent figures.

Memory 106 further includes a display module 126. Display module 126 maybe configured to generate a display for a user including the generatedx-ray image. Display module 126 may further be configured to generate auser interface for display on a display 130 that allows a user tointeract with the x-ray image, as described with reference to FIGS. 8-9.

System 100 further includes an input/output (I/O) interface 108. I/Ointerface 108 may be configured to receive information from an imagingsystem 132, and to receive information from and transmit information toan external display 130. I/O interface 108 may be configured to transmitone or more x-ray images for display on display 130, either wirelesslyor via a wired connection. Display 130 may be any type of display, suchas a display for a computer or other device. An example of an x-rayimage that may be displayed via display 130 is shown in greater detailin FIG. 9. I/O interface 108 may further receive inputs via display 130,an input device (e.g., keyboard, mouse, touch on a touchscreen, etc.)associated with display 130, other peripheral devices, and/or othersystems contained within a broader surgical system platform. System 100and more particularly the modules of system 100 may be configured tointerpret the inputs and generate x-ray images based on the inputs.

Referring again to FIG. 2, a flow chart of the high-level x-rayvisualization process 200 for generating an x-ray image is shown.Process 200 may generally be configured to create an x-ray image basedon a patient's CT scan, segmented bone models, created by any meansknown in the art, and a preoperative plan.

Process 200 may generally include, after clearing attenuation buffer 118and thickness buffer 120 (steps 202, 204), a volume ray casting process206. Ray casting process 206 may be executed by, for example, volume raycasting module 112. Ray casting process 206 may generally includecreating an x-ray image from a CT scan by casting a ray from an originpoint 608 through the bounding box of the CT volume for each pixel inthe image from the CT scan. The attenuation computed from the CT valuesalong the rays is accumulated. An x-ray image created by the volume raycasting process 206 is illustrated in image 300 of FIG. 3A. Image 300 isan x-ray view of the CT scan before any manipulation of the image hasoccurred.

Ray casting process 206 may also generally include, using the sameviewing parameters, creating an image of the CT volume inside certain ofthe segmented bone models selected for manipulation, for example bothfemur bones, as in an exemplary embodiment. The accumulated attenuationvalues may then be subtracted from the previous computed attenuation, toassist with surgical planning and any necessary manipulation of theanatomy shown in the x-ray image. Referring to image 310 of FIG. 3B, thex-ray image illustrated shows the result of subtracting the accumulatedattenuation values. For example, for a segmented femur bone model, thefemur bones are shown “subtracted” from the x-ray image.

In order to obtain an x-ray image of the patient's anatomy in a desiredposition, ray casting process 206 may also generally include creating animage of the CT volume inside bone models that have been translated,rotated, resected, and/or otherwise modified. In one embodiment thesemodifications are made according to a preoperative plan. The accumulatedattenuation values may then be added to the previous computedattenuation in the desired position. Referring also to image 320 of FIG.3C, the x-ray image illustrated shows the result of adding theaccumulated attenuation values. For the femur bone example illustratedin the figures, the virtually modified femur bones are added back intothe x-ray image. In the illustrated embodiment, the mechanical axes,which may be defined relative to the segmented bone model, are alignedto the pelvic midline axis and the operative side femur bone model isresected and reduced based on a preoperative plan.

After ray casting process 206, process 200 includes an attenuation modelprocess 208 in which attenuation models are drawn. Process 208 maygenerally include creating an image of the implant models, where theattenuation is proportional to the aggregate view-dependent thickness ofthe models and the implant model is placed according to a preoperativeplan. The generated attenuation values are added to the attenuationcomputed in process 206. Referring to image 330 of FIG. 3D, the x-rayimage illustrated shows the result of process 208. Processes 206, 208will be described in greater detail below with reference to FIGS. 4 and7, respectively.

Process 200 further includes mapping the computed attenuation values tograyscale color (step 210) and providing the x-ray image with the colorinformation to a screen or other display 130. Step 210 utilizes data inattenuation buffer 118 generated during ray casting process 206 and datain thickness buffer 120 generated during attenuation model process 208.

By executing process 200, x-ray images, such as those shown in images310, 320, and 330 of FIGS. 3B-3D, are generated that illustrate rotatedor otherwise manipulated features (e.g., the femur bone in image 320),and/or the planned position of an implant model (e.g., the implant modelin image 330). The features are shown in order to provide additionalassistive views for a surgeon or other medical professional forpreparation for surgery or for other medical reasons. The ray castingprocess may generally be configured to manipulate the features in thex-ray image, and the attenuation model process may generally beconfigured to illustrate such changes and features relevant to theprocedure.

Referring now to FIG. 4, ray casting process 206 is described in greaterdetail. Ray casting process 206 may be executed for an entire CT volume,and for a number of segmented bone models to be used to modify theinitial x-ray image. After selecting the next model (step 402), whichmay be, for example, an entire CT volume bounded by a cube or asegmented bone model, process 206 includes executing three renderingpasses. First, the front faces of the model are drawn into front buffer122 (step 404). This stores the world space coordinates of the frontfacing intersections 610 of the model surface and each ray 606 used instep 408, as discussed below. Also, the back faces of the model aredrawn into back buffer 124 (step 406). This stores the world spacecoordinates of the back facing intersections 612 of the model surfaceand each ray 606 used in step 408. Also, a screen space rectangle 602(as illustrated in FIG. 6) may be drawn to execute the GLSL shader forthe ray casting algorithm.

Ray casting process 206 further includes ray casting, and computing andsaving an accumulated attenuation resulting from the ray casting(process 408). Process 408 is described in greater detail in FIG. 5. Theresulting accumulated attenuation is stored in attenuation buffer 118,and process 206 moves on to check if there are more models to process(step 410).

Referring to FIG. 5, process 408 of computing and saving an accumulatedattenuation first includes initializing various parameters, such as rayposition, direction, and working volume distance (step 502). Step 502may include looking up the world space coordinates of the front and backfacing intersections 610, 612 of the model from buffers 122, 124. Theray position (e.g., a starting point of the ray 606), direction of theray, and the working volume distance of the ray is computed, and aseparate length variable is initialized to zero. The working volumedistance for each ray 606 may be computed as the distance along the ray606 between the front facing intersection 610 and the back facingintersection 612. Process 408 further includes checking if the workingvolume distance is not a valid number (e.g., infinity, not a number(NaN) or some other invalid value) (step 504).

Process 408 further includes looking up a data value and computing andaccumulating the attenuation (step 506). The activities of step 506 areillustrated in FIGS. 6A-B. FIG. 6A is an illustration 600 of an examplescreen space rectangle 602 and volume 604 for a model, and FIG. 6B is anillustration 620 of a top-down view of ray 606 going through volume 604.Step 506 first includes retrieving the 3D model from buffer 414 wherethe model is stored. To obtain the data value, a ray 606 with aspecified ray position and direction is sent from an origin point 608.Each ray 606 is sent from the origin point 608, through the center of arespective pixel in screen space rectangle 602, then through thebounding box of the volume 604. In one embodiment, a ray 606 may becomputed for each pixel in the screen space rectangle 602. In anotherembodiment, multiple rays 606 may be computed for each pixel in thescreen space rectangle 602, and the attenuation or color of the pixel iscomputed as the average of the attenuation or color from the multiplerays associated with each respective pixel. The ray caster moves alongray 606 at the given sampling distance 622 from the front facing side ofthe volume to the back facing side of the volume. Sampling distance 622should be selected to provide acceptable visualization, for example,choosing a sampling distance that is too coarse may result in theappearance of artifacts and spaces due to the difficulty of blendingbetween one sample and the next. The first sample may be taken at thefront facing intersection 610. At each step (e.g., at each samplingdistance 622), the ray caster samples the volume to obtain aninterpolated CT value. The CT value is converted to an attenuationcoefficient (described below with respect to the transfer function andmore specifically equations (18) and (19)). The CT value is accumulatedfor each sampling distance. The accumulated CT values may be representedas accumulated attenuation (A):

A=Σμ(p _(k))d  (1)

where μ(p_(k)) is the attenuation coefficient computed from the CT valuev(p_(k)) at a sampling location (p_(k)) along ray 606 and d is the steplength (e.g., sampling distance 622).

After each step the position of ray 606 is updated (for advancing ray606 through the volume of volume 604). The length variable is increasedby sampling distance 622 as well. If the length variable is not greaterthan the computed working volume distance (step 508), then process 408includes returning to step 506 for advancing the sampling position alongthe ray in volume 604. Once the length variable is greater than thecomputed working volume distance, the accumulated attenuation may besaved in attenuation buffer 118 (step 510). If attenuation has beencalculated, or an NaN or infinity determination has been made, for eachpixel in the screen space rectangle 602 process 408 may terminate,otherwise the process may continue for each remaining pixel in thescreen space rectangle 602. In one embodiment process 408 may beexecuted for each pixel in parallel by processor 104. The result ofprocess 408 is an accumulated attenuation stored in attenuation buffer118 for each pixel in the screen space rectangle 602 that is to be usedin generating the X-ray image for display. Attenuation buffer 118 isgenerally configured to store additive and subtractive accumulatedattenuation values as described below.

The volume ray casting process of step 506 supports arbitrary boundingmodels such as closed oriented manifold surfaces. For example, togenerate an X-ray view of a femur only, the segmented femur model may beused as the bounding box for the ray casting component. An arbitrarynumber of bounding models may be added to the visualization. Theaccumulated attenuation from each bounding model is either added orsubtracted from the total attenuation, depending on the type of model.Subtracting the accumulated attenuation is used to mask the contributionof a given bone in the X-ray image (as shown in FIG. 3B). Additive andsubtractive models may be accumulated separately:

A ⁺=Σμ⁺(p _(k))d  (2)

A ⁻=Σμ⁻ f(p _(k))d  (3)

The accumulated attenuation is converted to greyscale color (step 210):

c=1−exp(−A)  (4)

The color calculation may be modified to handle subtractive models:

c=1−exp(−A ⁺ +A ⁻)  (5)

Although Equation 5 includes a negative A⁺ added to a positive A⁻, asused herein this and similar operations are considered a subtraction ofA⁻ values from A⁺ values, as this operation is performed within anegative exponential function. In a similar manner, this and similaroperations could also be considered an addition, as used herein, of A⁺values to A⁻ values. The result being that A⁺ values tend to increasethe brightness of their respective pixels, while A⁻ values tend todecrease the brightness of their respective pixels. In an alternativeembodiment in which it may be desirable for more radiodense volumes toappear darker, and less radiodense volumes to appear lighter, the signsin front of A⁺ and A⁻ may be interchanged without altering the nature ofaddition and subtraction operations as used herein. The calculated color(c) may then be utilized to display a grayscale image. For example, inan 8-bit RGB display, the calculated color (c) may be utilized tocalculate Red, Green, and Blue values according to:

Red=255c  (6)

Green=255c  (7)

Blue=255c  (8)

As mentioned above, the CT value v(p_(k)) may be converted to anattenuation coefficient value μ(p_(k)) via a transfer function.Attenuation of X-ray intensity through homogenous materials ischaracterized by the Beer-Lambert law:

I=I ₀exp(−μΔx)  (9)

I₀ is the incoming intensity, I is the outgoing intensity, μ is thelinear attenuation coefficient representing the radiodensity of thematerial, and Δx is the distance the X-ray beam travels in the material.For inhomogeneous media, the equation may be approximated by a discretesummation, according to the following equation:

I=I ₀exp(−Σμ_(k) Δx)  (10)

Each line segment is assumed to be the same length crossing homogeneousmaterial with a constant attenuation coefficient μ_(k).

In radiology the Hounsfield scale is used as a standardized way ofcharacterizing the radiodensity of materials. The relationship betweenthe Hounsfield unit (HU) and the linear attenuation coefficient isexpressed by the following equation:

HU=1000*(μ−μ₀)/μ₀  (11)

where μ₀ is the linear attenuation coefficient of water. Attenuation isa function of incident X-ray photon energy. For example, for a 100 keVX-ray beam, μ₀=0.17 cm⁻¹, which means that 1 cm of water attenuates1−e^(−0.17)=15.6% of the photons in the beam. Under the same conditions,if an attenuation coefficient in a bone is given as μ=0.3 cm⁻¹, thisresults in an HU value of 765. In general, the HU value for bone rangesfrom 700 for cancellous to 3000 for a cortical bone.

CT values may be stored in DICOM (digital imaging and communications inmedicine) files. The CT values (v) are related to the HU values asfollows:

HU=v*slope+intercept  (12)

where the slope and intercept are parameters of the scanner and arestored in the data files. The slope and intercept values may differbased on various standards of different manufacturers.

The combination of equations (11) and (12) yields that the relativeattenuation coefficient is a linear function of the CT values:

μ/μ₀=max(α*v+β,0)  (13)

where α=slope/1000 and β=intercept/1000+1. Since the lower end of the CTdata value range is either zero or negative, additional clamping isneeded to ensure that the computed attenuation coefficient is anon-negative number.

A characteristic property of X-ray images is that tissue structures withhigher X-ray attenuation appear brighter in the image. To highlight orsuppress tissue structures in the generated X-ray visualization, the HUvalues are rescaled in a process called windowing:

HU′=clamp((HU−HU₀)/(HU₁−HU₀),0,1)*(HU_(max)−HU_(min))HU_(min)  (14)

where HU₀ and HU₁ specify the window range and HU_(min) and HU_(max) arethe minimum and maximum HU values from the data. Substituting equation(9) into equation (11) yields that windowing can be performed directlyon the CT values:

v′=clamp((v−v ₀)/(v ₁ −v ₀),0,1)*(v _(max) −v _(min))+v _(min)  (15)

where v_(min) and v_(max) are the minimum and maximum CT values in thedata.

Windowing rescales the CT value range, so tissues with CT values belowv₀ are suppressed and tissues with CT values above v₁ are highlightedwith a smooth transition for tissues with CT values between v₀ and v₁.Windowing allows the user to include only a selected CT value range inthe visualization.

A user interface (see FIGS. 8A-D and 9) may include brightness andcontrast sliders in an icon toolbar that control which tissue structuresare highlighted in the generated X-ray image. The window for suchstructures is computed according to:

v ₀ =v _(min)+(v _(max) −v _(min))*k ₀  (16)

v ₁ =v _(min)+(v _(max) −v _(min))*k ₁  (17)

where:

k ₁=(1−B)*1.25  (18)

k ₀ =C*k ₁  (19)

and 0≦B, C≦1 are the values of the brightness and contrast sliders.

To simplify the computations, equations (10) and (12) may be combined:

μ=max(clamp(v,v ₀ ,v ₁)*v _(scale) +v _(offset),0)  (20)

where:

v _(scale)=(v _(max) −v _(min))/(v ₁ −v ₀)*α*μ₀  (21)

v _(offset) =v _(min)*α*μ₀+β*μ₀ −v ₀ *v _(scale)  (22)

Equations (20), (21) and (22) are the equations that may be used toconvert the CT values obtained in process 408 to attenuation values. Theattenuation values are then accumulated as described with reference toequations (2) and (3).

The IGS (image guided system) files used may contain data values thatare not identical to the original CT values from the scanner. During theDICOM to IGS conversion process, the original CT values are rescaledusing the scale and offset parameters in the DICOM header resulting instandard HU values. Next, the HU values are modified using the windowingparameters in the DICOM header if the average HU value falls within thewindow. Otherwise, the data is shifted so the smallest HU value ismapped to zero in the output. This process may prevent recovery of theHU values, because it is not clear from the IGS header which conversionhas been applied. To accommodate both conversions, both equations (21)and (22) are used with slope set to 1 and intercept set to −1000,resulting in α= 1/1000 and β=0. The max function in equation (20) is notnecessary in such an implementation.

Referring to FIG. 7, process 208 for drawing constant attenuation modelsis described in greater detail. Process 208 may be executed after a raycasting process in which attenuation values are stored in attenuationbuffer 118. Process 208 may be executed for a number of models to beused in the x-ray image generation process. After selecting the nextmodel (step 702), all triangle faces of the model are drawn (step 704).The back facing depth values are subtracted from and the front facingdepth values are added to the values in thickness buffer 120. Afterdrawing the constant attenuation models in process 208, thickness buffer120 contains the aggregate view dependent thickness of the constantattenuation models. Process 208 repeats for all models to be drawn, andterminates after the last model has been rendered (step 706).

Since implant components (that are part of a preoperative plan) are notpart of the CT volume, the data may be added in a separate renderingpass. In one embodiment, for the sake of speed it is assumed that eachcomponent of the implant is made of the same material, a view-dependentthickness t may be computed for each implant component. The accumulatedattenuation (A^(imp)) is then computed from the thickness:

A ^(imp) =μ*t  (23)

where μ is the linear attenuation coefficient of the implant materialcomputed from the corresponding HU value as:

μ/μ₀=HU/1000+1  (24)

The color calculation of equation (5) may be modified to include thecontribution from all implant components:

c=1−exp(−A ⁺ +A ⁻ −A ^(imp))  (25)

Contributions from the implant components are not affected by thebrightness and contrast sliders, according to an exemplary embodiment.

Referring also to FIGS. 8A-D, the effect of the various brightness andcontrast values for an x-ray image is illustrated. The user may adjustthe brightness and contrast sliders on a user interface (FIG. 9) to finetune the look of the X-ray image and account for the differences in databetween various scanners. This capability may be highly useful to themedical professional to view various features of the anatomy, such asviewing a representation of the patient's skin, bone alone, bone andsoft tissue, etc. to assist in surgical planning or provide otherinformation helpful to a procedure. In image 800 of FIG. 8A, thebrightness and contrast values are set to 0. In image 810 of FIG. 8B,the brightness and contrast values are set to 0.5. In image 820 of FIG.8C, the brightness and contrast values are set to 0.15 and 0.25,respectively. In image 830 of FIG. 8D, the brightness and contrastvalues are set to 0.6 and 0.75, respectively. In one embodimentbrightness values may generally range from 0.0 to 0.99 and contrastvalues may range from 0.0 to 1.0.

Referring to FIG. 9, a user interface 900 on which an x-ray image may bedisplayed is shown, according to an exemplary embodiment. User interface900 may be a user interface displayed to a user as part of apreoperative planning page or mode. User interface 900 may be providedin a separate viewing mode in addition to a 3D view, CT slicer view, and3D slicer view.

The user may activate the x-ray view when the user toggles on an x-rayview toggle button in the icon toolbar or elsewhere on user interface900. User interface 900 may include brightness and contrast sliders foradjusting the visual appearance of the image, as described in FIGS.8A-D. As illustrated in FIG. 9, one slider may be provided with thefunctionality to toggle between brightness and contrast controls. Userinterface 900 may further include various controls for supporting aninteractive view manipulation, including rotating, panning, or zoomingthe view of the x-ray image. Use interface 900 may display various linesthat indicate various features. For example, in FIG. 9, lines indicatingthe anterior superior iliac spine (ASIS) and pelvis midline shown in thedefault orientation are illustrated. The lesser trochanter landmark andhip length indicator lines are also illustrated. Implant positioning issupported, either by clicking the implant positioning buttons or byclicking and dragging the implant model in the cup plan and stem planmodes.

One alternative approach is to use a rasterized representation for thebone and implant models, similarly to a segmentation mask. While thevisual quality would not be affected, the extra texture lookups requiredto use the raster data could result in reduced rendering performance.

Another alternative approach to the x-ray image manipulation isimplementing implant visualization and rotation correction bymanipulating the data values in the CT volume during segmentation. Suchan approach requires moving and calculating large amounts of data, andmay be constrained by the resolution of the CT scan.

A third alternative approach may first include computing the accumulateddata values along the viewing ray:

v _(sum) =Σv(p _(k))  (26)

Next, the accumulated values are normalized to the range of the inputdata values:

v _(norm) =v _(sum) /v _(maxsum) *v _(max)  (27)

where v_(maxsum) is the maximum of all v_(sum) values computed for theX-ray image and v_(min) is assumed to be zero. The normalization may behelpful to reduce the sensitivity of the computation to the selectedstep size.Finally, the normalized accumulated values are mapped to grayscale coloraccording to:

c=(clamp(v _(norm) ,v ₀ ,v ₁)−v ₀)/(v ₁ −v ₀)  (28)

where v₀ and v₁ are computed using equations (13) and (14). Since thebrightness and contrast values are only used in equation (25) to controlhow the normalized accumulated values are mapped to color, theimplementation does not need to perform the accumulation step ofequation (23) when the user changes the brightness and contrast valuesin the application.

By creating a two-dimensional x-ray image from data, such as dataacquired during a CT scan, and performing a method of x-rayvisualization according to the present disclosure, a medicalprofessional may continue to use the x-ray visualization with whichhe/she is familiar, with added capabilities for manipulating the imageto assist in surgical planning and performance.

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the exemplaryembodiments without departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on any machine-readable media for accomplishing variousoperations. The embodiments of the present disclosure may be implementedusing existing computer processors, or by a special purpose computerprocessor for an appropriate system, incorporated for this or anotherpurpose, or by a hardwired system. Embodiments within the scope of thepresent disclosure include program products comprising machine-readablemedia for carrying or having machine-executable instructions or datastructures stored thereon. Such machine-readable media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer or other machine with a processor. By way of example,such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROMor other optical disk storage, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to carry or storedesired program code in the form of machine-executable instructions ordata structures and which can be accessed by a general purpose orspecial purpose computer or other machine with a processor. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a machine, the machine properly views theconnection as a machine-readable medium. Thus, any such connection isproperly termed a machine-readable medium. Combinations of the above arealso included within the scope of machine-readable media.Machine-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing machines to perform a certain function orgroup of functions.

Although the figures may show a specific order of method steps, theorder of the steps may differ from what is depicted. Also two or moresteps may be performed concurrently or with partial concurrence. Suchvariation will depend on the software and hardware systems chosen and ondesigner choice. All such variations are within the scope of thedisclosure. Likewise, software implementations could be accomplishedwith standard programming techniques with rule based logic and otherlogic to accomplish the various connection steps, processing steps,comparison steps and decision steps.

What is claimed is:
 1. A method of creating an image, comprising:retrieving three-dimensional image data of an anatomy; retrieving amodel of a portion of the anatomy; associating the model with thethree-dimensional image data such that the model defines a boundedvolume within the three-dimensional image data corresponding to theportion of the anatomy; and creating a virtual radiograph of the portionof the anatomy, wherein creating the virtual radiograph comprises:casting a plurality of rays from an origin point through the boundedvolume; sampling, for each ray, the bounded volume at a plurality ofsampling steps along the ray, the sampling steps separated by a samplingdistance; and calculating, for each ray, an accumulated attenuationvalue of the bounded volume along the ray based on the samples.
 2. Themethod of claim 1, wherein the portion of the anatomy is a first portionof the anatomy, the model is a first model, and the bounded volume is afirst bounded volume, the method further comprising: retrieving a secondmodel of a second portion of the anatomy, wherein the second portion ofthe anatomy is a subset of the first portion of the anatomy; andassociating the second model with the three-dimensional image data suchthat the second model defines a second bounded volume within thethree-dimensional image data corresponding to the second portion of theanatomy, wherein the second bounded volume is a subset of the firstbounded volume; wherein creating the virtual radiograph furthercomprises: casting a plurality of rays from the origin point through thesecond bounded volume; sampling, for each ray, the second bounded volumeat a plurality of sampling steps along the ray, the sampling stepsseparated by the sampling distance; calculating, for each ray, anaccumulated attenuation value of the second bounded volume along the raybased on the samples; and subtracting the accumulated attenuation valuesfor the second bounded volume from the accumulated attenuation valuesfor the first bounded volume.
 3. The method of claim 2, furthercomprising: receiving a modification of the second model; whereincreating the virtual radiograph further comprises: modifying theaccumulated attenuation values for the second bounded volume accordingto the modification of the second model; and adding the modifiedaccumulated attenuation values to the accumulated attenuation values forthe first bounded volume.
 4. The method of claim 3, wherein themodification of the second model comprises at least one of a translationof the second model, a rotation of the second model, or a resection ofthe second model.
 5. The method of claim 3, wherein the modification ofthe second model is according to a preoperative plan.
 6. The method ofclaim 1, further comprising: retrieving a model of an implant; whereincreating the virtual radiograph further comprises: selecting a view forthe implant model; determining a view-dependent thickness for theimplant model; calculating accumulated attenuation values for theimplant model for the selected view, based on the view-dependentthickness; and adding the accumulated attenuation values for the implantto the accumulated attenuation values for the bounded volume.
 7. Themethod of claim 6, wherein the implant is at least one component of ahip implant.
 8. The method of claim 6, wherein the accumulatedattenuation values for the implant are added to the accumulatedattenuation values for the bounded volume according to a preoperationalplan.
 9. The method of claim 1, further comprising: converting eachaccumulated attenuation value to a color; and displaying an image of thevirtual radiograph based the converted colors.
 10. The method of claim1, wherein the model is a segmented bone model.
 11. An image generationsystem, comprising: an input/output interface; a display coupled to theinput/output interface; and a processing circuit having a processor anda memory, the processing circuit configured to: retrievethree-dimensional image data of an anatomy; retrieve a model of aportion of the anatomy; associate the model with the three-dimensionalimage data such that the model defines a bounded volume within thethree-dimensional image data corresponding to the portion of theanatomy; create a virtual radiograph of the portion of the anatomy,wherein creating the virtual radiograph comprises: casting a pluralityof rays from an origin point through the bounded volume; sampling, foreach ray, the bounded volume at a plurality of sampling steps along theray, the sampling steps separated by a sampling distance; andcalculating, for each ray, an accumulated attenuation value of thebounded volume along the ray based on the samples; and display an imageof the virtual radiograph on the display.
 12. The system of claim 11,wherein the portion of the anatomy is a first portion of the anatomy,the model is a first model, and the bounded volume is a first boundedvolume, and wherein the processing circuit is further configured to:retrieve a second model of a second portion of the anatomy, wherein thesecond portion of the anatomy is a subset of the first portion of theanatomy; associate the second model with the three-dimensional imagedata such that the second model defines a second bounded volume withinthe three-dimensional image data corresponding to the second portion ofthe anatomy, wherein the second bounded volume is a subset of the firstbounded volume; and create the virtual radiograph of the first portionof the anatomy by: casting a plurality of rays from the origin pointthrough the second bounded volume; sampling, for each ray, the secondbounded volume at a plurality of sampling steps along the ray, thesampling steps separated by the sampling distance; calculating, for eachray, an accumulated attenuation value of the second bounded volume alongthe ray based on the samples; and subtracting the accumulatedattenuation values for the second bounded volume from the accumulatedattenuation values for the first bounded volume.
 13. The system of claim12, wherein the processing circuit is further configured to: receive amodification of the second model; and create the virtual radiograph by:modifying the accumulated attenuation values for the second boundedvolume according to the modification of the second model; and adding themodified accumulation attenuation values to the accumulated attenuationvalues for the first bounded volume.
 14. The system of claim 13, whereinthe modification of the second model comprises at least one of atranslation of the second model, a rotation of the second model, or aresection of the second model.
 15. The system of claim 11, wherein themodification of the second model is according to a preoperative plan.16. The system of claim 11, wherein the processing circuit is furtherconfigured to: retrieve a model of an implant; and create the virtualradiograph by: selecting a view for the implant model; determining aview-dependent thickness for the implant model; calculating accumulatedattenuation values for the implant model for the selected view, based onthe view-dependent thickness; and adding the accumulated attenuationvalues for the implant to the accumulated attenuation values for thebounded volume.
 17. The system of claim 16, wherein the implant is atleast one component of a hip implant.
 18. The system of claim 16,wherein the processing circuit is configured to add the accumulatedattenuation values for the implant to the accumulated attenuation valuesfor the bounded volume according to a preoperational plan.
 19. Thesystem of claim 11, wherein the processing circuit is further configuredto: convert each accumulated attenuation value to a color; and displaythe image of the virtual radiograph based on the converted colors. 20.The system of claim 11, wherein the model is a segmented bone model.